Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Making models smaller and faster: quantization, distillation, pruning, sparsity and kernel-level work.
Signals: quantization, model-compression, pruning, knowledge-distillation, gptq, awq, bitsandbytes, sparsity
187 results
Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012
(AAAI' 20) A Python Toolbox for Machine Learning Model Combination
Python package for stacking (machine learning technique)
Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms
Homomorphic machine learning
This repository is for my YT video series about optimizing a Tensorflow deep learning model using TensorRT. We demonstrate optimizing LeNet-like model and YOLOv3 model, and get 3.7x and 1.5x faster for the former and the latter, respectively, compared to the original models.
AKG (Auto Kernel Generator) is an optimizer for operators in Deep Learning Networks, which provides the ability to automatically fuse ops with specific patterns.
Sublinear memory optimization for deep learning, reduce GPU memory cost to train deeper nets
Ranger deep learning optimizer rewrite to use newest components
Generate 8-bit chiptunes with deep learning
Sublinear memory optimization for deep learning. https://arxiv.org/abs/1604.06174
Embedded and mobile deep learning research resources
Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase
Codebase for "SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems"
A New Optimization Technique for Deep Neural Networks
Binarized Neural Network (BNN) for pytorch
Open Neural Network Compiler
The calflops is designed to calculate FLOPs、MACs and Parameters in all various neural networks, such as Linear、 CNN、 RNN、 GCN、Transformer(Bert、LlaMA etc Large Language Model)
AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.
A flexible and efficient deep neural network (DNN) compiler that generates high-performance executable from a DNN model description.
List of papers related to neural network quantization in recent AI conferences and journals.
PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks
Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)
Collection of recent methods on (deep) neural network compression and acceleration.
24,535 repositories in the index in total.
